Download lm-quant-toolkit/test.py from chen459664/quantization2: direct link, hf CLI and curl.
- Browser
- Download file 575 Bytes
-
https://huggingface.co/chen459664/quantization2/resolve/9052d77a5566e7f665b660367299b5b4d22a63b2/lm-quant-toolkit/test.py
- Command line
-
hf download hf://chen459664/quantization2@9052d77a5566e7f665b660367299b5b4d22a63b2/lm-quant-toolkit/test.py
-
curl -L -o test.py https://huggingface.co/chen459664/quantization2/resolve/9052d77a5566e7f665b660367299b5b4d22a63b2/lm-quant-toolkit/test.py
575 Bytes
| import pandas as pd | |
| import json | |
| import os | |
| import argparse | |
| parser = argparse.ArgumentParser(description="") | |
| parser.add_argument( | |
| "--model", | |
| type=str, | |
| default="Llama-3.1-70B-Instruct", | |
| ) | |
| args = parser.parse_args() | |
| file_path =f'/mnt/bn/life-mllm/users/cxr/quantization/lm-quant-toolkit/tmp/kurtosis-dump/{args.model}/kurtosis-models.csv' | |
| df = pd.read_csv(file_path) | |
| kurtosis_means = df.groupby("layer")["kurtosis"].mean().tolist() | |
| with open(f"kurtosis_means/kurtosis_means-{args.model}.json", "w") as f: | |
| json.dump(kurtosis_means, f, indent=4) | |